Ieee-Caa Journal of Automatica Sinica最新文献_第3页

Necessary and/or Sufficient Conditions of Controllability of Networked Sampled-Data Systems with Nonequidistant Sampling 非等距采样网络数据系统可控性的必要或充分条件

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2026.125906

Zhaofei Li;Fei Hao

引用次数: 0

Output Consensus for Heterogeneous Two-Time-Scale Multiagent Systems Under DoS Attacks: A Multi-Index Case 异构双时间尺度多智能体系统在DoS攻击下的输出一致性：一个多指标案例

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-10-01 DOI: 10.1109/JAS.2026.125912

Ying Zhang;Linna Zhou;Lei Ma;Chunyu Yang;Guoqing Wang;Wei Dai

{"title":"Output Consensus for Heterogeneous Two-Time-Scale Multiagent Systems Under DoS Attacks: A Multi-Index Case","authors":"Ying Zhang;Linna Zhou;Lei Ma;Chunyu Yang;Guoqing Wang;Wei Dai","doi":"10.1109/JAS.2026.125912","DOIUrl":"https://doi.org/10.1109/JAS.2026.125912","url":null,"abstract":"This article studies the output consensus issue for a class of heterogeneous two-time-scale multiagent systems (HTTS-MASs) under denial-of-service (DoS) attacks. A novel output consensus control framework, integrating a resilient distributed observer and a composite controller, is built as the first attempt for HTTSMASs. By establishing a DoS attack impact interval for each communication channel, the resilient distributed observer based on asynchronous sampling is designed to resist DoS attacks. Given the inherent two-time-scale characteristics, solving the regulator equations (REs) of original HTTSMASs often leads to ill-conditioned numerical issues. To overcome this challenge, singular perturbation theory is employed to decouple the output consensus problem into a multi-index control problem for slow and fast subsystems. Specifically, a slow sub-controller is designed to achieve output tracking based on the solution of the slow subsystem's REs, while a fast sub-controller is designed to guarantee the fast subsystem's stability. Finally, a numerical example and an application involving a permanent magnet synchronous motor are presented to verify the effectiveness of the designed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 9","pages":"2109-2118"},"PeriodicalIF":18.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cloud-Based Formation Tracking Control of Networked Multi-Agent Systems with Network Delay Compensation and Prescribed Performance Guarantee 基于网络延迟补偿和性能保证的网络化多智能体系统云编队跟踪控制

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2025.125645

Rui-Min Zhou;Yingying Pang;Chang-Bing Zheng;Lina Yao

引用次数: 0

Potential-Guided Connected Network for Tiny Structure Segmentation in Medical Images 用于医学图像微小结构分割的电位引导连接网络

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2025.125705

Chouyu Chen;Yaotong Song;Junyan Yi;Lijun Guo;Zhenyu Lei;Shangce Gao

{"title":"Potential-Guided Connected Network for Tiny Structure Segmentation in Medical Images","authors":"Chouyu Chen;Yaotong Song;Junyan Yi;Lijun Guo;Zhenyu Lei;Shangce Gao","doi":"10.1109/JAS.2025.125705","DOIUrl":"https://doi.org/10.1109/JAS.2025.125705","url":null,"abstract":"Medical images provide essential information for diagnosing and monitoring various diseases and systemic disorders. With advancements in deep learning and neural networks, numerous methods have been proposed to achieve high-level medical image segmentation results. However, the variability of tiny structures and their high similarity to the background often lead to mis-segmentation in existing methods. To mitigate these challenges, we propose a potential-guided connected network (PCNet) that integrates an innovative dual soft-hard constraint strategy, combining two different progressive supervisions. This strategy modulates the ability of network to differentiate between well-defined and ambiguous structures through a hyper-parameter, thereby enhancing its capability to detect tiny structures. Furthermore, PCNet is composed of two key modules, including the intermediate generation (IG) module and the progressive inference (PI) module. The IG module produces a range of outputs with varying segmentation potentials using a novel serial architecture, which serves as the foundational input for progressive reasoning in the PI module. The PI module, leveraging the outputs of the IG module, is designed to progressively extract comprehensive contextual information, ultimately producing refined segmentation results. PCNet is evaluated on several publicly available datasets, including DRIVE, MoNuSeg, CoNIC, FIVES, and GlaS, achieving accuracy of 96.92%, 90.29%, 93.93%, 98.82%, and 92.00%, respectively. Extensive experiments demonstrate that our model outperforms the current state-of-the-art methods for tiny structure segmentation in medical images.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 8","pages":"1826-1841"},"PeriodicalIF":18.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human-in-the-Loop Control for Industrial IoT Systems: A Modified FAS Predictive Control 工业物联网系统的人在环控制：一种改进的FAS预测控制

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2025.125819

Da-Wei Zhang;Guo-Ping Liu

引用次数: 0

A New Result of Prescribed-Time Control for Uncertain Nonlinear Systems and its Applications to Higher-Order Tracking 不确定非线性系统规定时间控制的一个新结果及其在高阶跟踪中的应用

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-27 DOI: 10.1109/JAS.2025.125987

Liuliu Zhang;Xianglin Liu;Cheng Qian;Changchun Hua

{"title":"A New Result of Prescribed-Time Control for Uncertain Nonlinear Systems and its Applications to Higher-Order Tracking","authors":"Liuliu Zhang;Xianglin Liu;Cheng Qian;Changchun Hua","doi":"10.1109/JAS.2025.125987","DOIUrl":"https://doi.org/10.1109/JAS.2025.125987","url":null,"abstract":"In this paper, the problem of the prescribed-time control for uncertain nonlinear systems is considered, and new design and analysis methods are presented. First, to evaluate the convergence of higher-order derivatives of the states and estimate the convergence rate of each state as time approaches the terminal time, a novel prescribed-time higher-order stability theorem is provided. Then, in accordance with the proposed criterion and the multivariate Faa di Bruno's formula, new design and analysis architectures are proposed for the adaptive prescribed-time control and the robust prescribed-time control, which avoid the widely encountered issue of indeterminate form limit analysis in the no-scaling prescribed-time control method, thus the benefits of the scaling and no-scaling approaches are taken together. In addition, the proposed strategies are applied to the development of the prescribed-time higher-order tracking controller, enhancing the smoothness of the tracking process. Finally, several simulation examples of a real system are given to illustrate the effectiveness and superiority of the algorithms.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 8","pages":"1904-1914"},"PeriodicalIF":18.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148822926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Multiagent Systems-Oriented Privacy Protection and Convergence Predefinition 面向非线性多智能体系统的隐私保护与收敛预定义

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2025.125969

Bingjie Ding;Peihao Du;Xiaojie Peng;Yan Lei;Hongyi Li

引用次数: 0

A Reference Vector-Guided and Generative Adversarial Network-Driven Competitive Swarm Optimizer for Large-Scale Multi-Objective Optimization 面向大规模多目标优化的参考矢量导向生成对抗网络驱动竞争群优化器

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2026.125849

Chunlei Li;Libao Deng;Liyan Qiao;Lili Zhang

{"title":"A Reference Vector-Guided and Generative Adversarial Network-Driven Competitive Swarm Optimizer for Large-Scale Multi-Objective Optimization","authors":"Chunlei Li;Libao Deng;Liyan Qiao;Lili Zhang","doi":"10.1109/JAS.2026.125849","DOIUrl":"https://doi.org/10.1109/JAS.2026.125849","url":null,"abstract":"Competitive swarm optimizers (CSOs) have demonstrated promising performance in addressing large-scale optimization challenges. However., they are often criticized for inefficient convergence when solving large-scale multi-objective optimization problems (LSMOPs) due to their competition and learning mechanisms being originally designed for single-objective scenarios. To overcome this limitation, this paper proposes a reference vector-guided and generative adversarial network (GAN)-driven CSO variant for LSMOPs. The algorithm introduces a dual-criteria competition mechanism to replace the conventional random pairwise competition, enabling more effective swarm division into winner and loser groups while preserving diverse search directions. Furthermore, it enhances particle update through two comprehensive learning strategies: a reference vector-guided update strategy that directs loser particles toward promising search directions in a self-supervised manner, coupled with a GAN-driven reproduction strategy where a GAN model is trained to capture the distribution patterns of high-performing winner particles, subsequently generating refined candidate solutions with improved quality and diversity. By synergizing the strong exploration of CSO with the efficient exploitation of GAN-based reproduction, the proposed algorithm achieves promising optimization performance. Experimental results demonstrate its superiority over seven state-of-the-art large-scale multi-objective optimization algorithms on both LSMOP benchmark problems and real-world applications.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 8","pages":"1952-1968"},"PeriodicalIF":18.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New AI for Quantum Computing: From Quantum Optimization to Quantum Intelligence 量子计算的新人工智能：从量子优化到量子智能

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2026.125765

Yonglin Tian;Xinyu Liu;Fei Lin;Lingxi Li;Xiaoxiang Na;Paul J. Werbos;S. N. Wendin

{"title":"New AI for Quantum Computing: From Quantum Optimization to Quantum Intelligence","authors":"Yonglin Tian;Xinyu Liu;Fei Lin;Lingxi Li;Xiaoxiang Na;Paul J. Werbos;S. N. Wendin","doi":"10.1109/JAS.2026.125765","DOIUrl":"https://doi.org/10.1109/JAS.2026.125765","url":null,"abstract":"How far are we from quantum computers that serve everyone? More than a century has passed since quantum mechanics reshaped our understanding of nature, and in 2025, the Nobel Prize in physics once again honored breakthroughs in quantum mechanics for macroscopic quantum tunneling, a sign that quantum theory is stepping from abstraction into the tangible world. Yet for most people, quantum computers still seem as distant as the early mainframes once were. When Thomas Watson of IBM predicted that only a handful of computers would suffice for global needs almost 80 years ago, few could imagine that within decades, personal computers would become household tools. Today, diverse prototypes are steadily scaling up in qubit number and control precision, from superconducting qubits to trapped ions and photonic chips. Meanwhile, the quantum processing unit (QPU) is beginning to merge seamlessly with CPUs and GPUs into a unified computational fabric. As advances in quantum computing, quantum optimization, and quantum Artificial Intelligence (AI) continue to emerge (as discussed below), a new wave of AI, especially autonomous intelligence, is rapidly unfolding [1], and its coevolution with quantum technologies is opening a promising pathway toward the next generation of intelligent systems under the paradigm of quantum intelligence.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 8","pages":"1779-1782"},"PeriodicalIF":18.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11669857","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Set-Membership Estimation and Its Application to the Design of an Interacting Multiple Model Estimator 非线性集隶属估计及其在交互多模型估计器设计中的应用

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-08-01 Epub Date: 2026-08-28 DOI: 10.1109/JAS.2025.125867

Hao Liu;Qing-Long Han;Zixin Huang;Yuzhe Li;Wei Wang

引用次数: 0